In a variety of biomedical applications, an electrical stimulus is applied to tissue in order to evoke a desired response. Examples of such electrical stimulus can be found in cardiac, evoked potential, and nerve testing applications. The stimulus can cause unwanted artifacts that can complicate the interpretation of recorded signals. This patent application describes a technique for removing these artifacts, focusing on application to the field of nerve conduction testing.
Nerve conduction studies (NCS) provide a reliable, accurate and sensitive means for detecting a variety of peripheral nervous system disorders. In NCS testing, a set of surface electrodes is placed against the skin overlying a nerve and a brief electrical stimulus is applied. If the electrical stimulus is of sufficient magnitude, it triggers a wave of membrane depolarization that spreads bi-directionally outward from the stimulus site. This wave of membrane depolarization can be detected with surface electrodes placed over the nerve at a site remote from the original stimulus site. For sensory nerves, this membrane depolarization signal is commonly referred to as a compound sensory nerve action potential (SNAP). This SNAP signal may be measured and analyzed. For motor nerves, the wave of membrane depolarization terminates at a neuromuscular junction (i.e., the motor endplate zone), causing depolarization of the muscle membranes and a resultant muscle contraction. In motor NCS, this response evoked in the muscle, which is generally referred to as a compound motor action potential (CMAP), is measured and analyzed.
NCS results are interpreted by comparing the patient's response characteristics to a normative reference that describes the range of values expected for healthy individuals. Prolongation of motor or sensory latencies can indicate nerve compression with injury to the nerve's myelin sheath, as can be seen in carpal tunnel syndrome (i.e., median nerve entrapment at the wrist) or ulnar neuropathy at the elbow. The CMAP and SNAP amplitudes are also clinically significant parameters. For example, low sural nerve SNAP amplitude is a reliable, accurate and sensitive indicator of polyneuropathy in diabetic patients.
The accuracy with which response parameters are measured critically influences NCS clinical utility. Unreliable parameter estimates' reduce NCS accuracy and may even lead to incorrect diagnoses.
A common problem in NCS is that a stimulus artifact (SA) can distort the nerve signal. This is particularly true for sensory studies (as compared to motor studies) inasmuch as sensory signals are smaller in amplitude and therefore may be more easily distorted. Several mechanisms can give rise to SA, but the stimulus artifact is generally the result of residual stimulus current spreading through the body tissue. The degree of SA observed in a test depends on the properties of the patient's skin, and the skin-electrode interface, among other parameters.
There are many clinical and non-clinical situations that call for rapid, reliable and low-cost NCS testing. Reliable automated devices have been introduced into the marketplace to assess neuromuscular function in primary care physician and small clinic settings. These automated NCS devices are designed to be used by personnel without specialized training. The apparatus and method described by Gozani in U.S. Pat. No. 5,976,094 is one such example of a device and method that is successfully used to make neuromuscular assessments of peripheral nerves many thousands of times every year. With the Gozani method and device, an NCS signal is evoked, recorded and analyzed by the device and the results are provided to the user. While automated NCS devices have proven highly successful in clinical applications, it is recognized that the removal or minimizing of stimulus artifacts would further improve the performance of the devices. For automated testing, it is necessary to minimize or remove the stimulus artifact in a manner which does not require significant user training or interaction.
Significant efforts have been made to remove or minimize stimulus artifacts in bioelectrical signals such as NCS.
The stimulus artifact is most easily handled when it does not overlap in time with the signal of interest. U.S. Pat. No. 6,768,924 and U.S. Patent Publication No. 2006/0173496 both teach methods for identifying and zeroing out segments of a bioelectrical signal that contains SA. These documents provide examples of a technique denoted as “hardware blanking”, a term which is used below. Others have proposed a software-based approach for accomplishing the same goal. All of these approaches are based on the concept of separating the stimulator and detector electrodes by a distance sufficient to time-separate the SA and the signal of interest. However, for NCS, the possible electrode sites are frequently constrained by anatomy. Thus, it is not always possible to separate the stimulator and detector electrodes by a distance sufficient to ensure that the signal of interest arrives after the stimulus artifact has decayed away.
In clinical practice, stimulus artifacts in NCS studies are often minimized by rotating the orientation of the stimulation electrodes. This approach has the effect of changing the electrical fields at the detector electrodes. It is often possible to find an electrode orientation which adequately stimulates the nerve but minimizes the stimulus artifact. The primary disadvantage of this approach is that it requires a highly skilled specialist to perform the NCS test. This is contrary to the goal of automated NCS testing, which seeks to use automated NCS test devices which require minimal user training and interaction.
Several patents teach related methods for reducing SA via electrode placement. U.S. Pat. No. 6,944,502 teaches a method for reducing SA in the measurements of auditory evoked potential by placing the detector electrodes perpendicular to the stimulator electrodes. However, this approach is not practical for NCS applications, since the anatomical differences between patients mean that a single electrode geometry will not be optimal for all patients. U.S. Patent Publication No. 2006/178706 teaches that SA may be reduced in ECG recordings by deploying multiple electrode pairs, and then choosing the electrode pair that minimizes SA. However, this approach generally requires more complicated sensors and data acquisition systems, and would increase the cost of an NCS study.
In another approach, adaptive signal processing methods are used to cancel SA based on information provided by a reference channel. This reference channel provides a measurement of the SA but should not contain any data from the signal of interest. The reference channel may be obtained by using off-nerve measurements, or by using stimuli that are low enough that no nerve response is triggered (see U.S. Pat. No. 6,936,012). Unfortunately, the usefulness of adaptive approaches may be limited, because a good reference channel may not be available (i.e., the reference channel may be contaminated by the signal of interest, or the SA in the reference channel may have a different morphology than that in the primary channel, or both). In addition, recording a reference channel increases hardware requirements and drives up the cost and complexity of NCS equipment.
Another class of signal processing methods involves modeling the stimulus artifact by fitting polynomials, splines, or exponential curves to the data. These shapes are empirically determined by the algorithm designer, and are not linked to physical parameters of the electronics or the stimulus. Once the estimated stimulus artifact has been determined by this modeling, it is subtracted from the data. While this type of approach has merit, it can be difficult to find simple shapes that can account for the SA morphology throughout the full NCS waveform. Thus, some researchers have reverted to piecewise curve fits. However, such piecewise curve fitting generally complicates the curve fitting procedure and can actually make it more prone to error.
The electronics of the automated NCS device can have a significant impact in shaping the SA morphology. In principle, the shaping of SA introduced by the electronics can be removed using deconvolution. However, as is known to those skilled in the art, waveform reconstruction using deconvolution is subject to errors when the input data is noisy. Thus, it has been suggested that extensive waveform averaging can be used to reduce noise prior to deconvolution. However, in the NCS application, such waveform averaging would require patients to receive additional electrical shocks, making NCS studies longer and less comfortable for the patients.